Complex systems or environments often require simulation or modeling as a way of determining costs, identifying potential sources of error, testing new design features, etc. In addition, forms of entertainment such as gaming often require similar types of resources and flexibility as that of complex system models. These resources include computational power, data storage, processes for efficient data transfer across networks, and processes to provide users with the ability to vary system or environment configurations (e.g., to change boundary conditions or constraints) in order to observe how the system or model changes.
Unfortunately, conventional systems or platforms for generating and enabling interactions with complex networks, simulations, models, or environments (including virtual environments, such as found in gaming experiences) are implemented in ways that limit their scalability, their ability to develop and incorporate learned behaviors, and their effectiveness for users as a result of latency problems when large amounts of data or content is transferred across a network.
These are important factors; for some types of systems or user experience, latency is a limiting factor. For example, virtual reality applications typically require low-latency interactions between a user and the environment in order to provide a satisfactory end user experience. However, if such an application is hosted on a remote server or platform, data transfer rates are impacted by network characteristics, resulting in a sub-optimal experience. For this reason, conventional virtual reality applications and complex simulations or models may not be able to be effectively hosted as a cloud-based service.
Conventional systems also typically fail to implement sufficient optimizations to reduce or more effectively manage CPU and/or resource consumption within a web-based or cloud platform application. This results in higher demands on platform and/or client devices and processes, and can lead to load balancing and other resource allocation problems.
Further, current Content Distribution Networks (CDN) face significant bandwidth constraints as a result of using conventional methods to handle larger volumes of data. This is partially the result of how data is stored and transferred; as a result, it is difficult to know whether information being removed from a file to reduce bandwidth constraints is important or not to the end user experience. As streaming video and other content delivery becomes more widespread, these constraints prevent the growth and adoption of business models based on those technologies.
Conventional systems and approaches also suffer from deficiencies with regards to data loss during compression, as data compression typically results in uniform data loss. This is undesirable, as lossy compression methods may not provide a satisfactory user experience on high definition displays. To minimize this problem, conventional systems may opt to perform only limited compression that does not significantly deteriorate the end user experience. However, this approach may not address the data transport issues that lead to experiencing latency when using the system.
Embodiments of the invention are directed toward solving these and other problems individually and collectively.